Ishtar Nyawira, a data science intern at the Pittsburgh Supercomputer Center shares how she is using deep learning and the GPU-accelerated Bridges supercomputer to automate the process of biological image annotation from high-resolution scanning electron microscope (SEM) imagery. The goal of the project is to ultimately understand how the neurons in our brains are wired.

Harvard graduate students at the Allen Institute for Brain Science spent months manually annotating zebrafish neurons in SEM imagery. “The students were working with nearly 5,000 zebrafish images and each of them had to annotate the neurons in the images and there are about 200 neurons per image — so that takes a lot of time and incredibly time consuming,” said Nyawira. “This is something we’re trying to automate, so students don’t have to spend so much time doing things like that and can better apply their skills elsewhere.”

Using the Tesla P100 GPUs on the Bridges supercomputer and the TensorFlow deep learning framework, Ishtar is training her models on SEM imagery of zebrafish larva and the mouse brain to recognize neurons without being confused about noise and the tissue inside of the images.

About Brad Nemire

Brad Nemire is on the Developer Marketing team and loves reading about all of the fascinating research being done by developers using NVIDIA GPUs. Reach out to Brad on Twitter @BradNemire and let him know how you’re using GPUs to accelerate your research. Brad graduated from San Diego State University and currently resides in San Jose, CA. Follow @BradNemire on Twitter